
Expected Project Results
The project is the interdisciplinary research project focusing on the enhancing the existing technologies for Service-oriented Computing and Technology Enhanced Learning.
The main scientific results of the proposed projects are:
- New methods for dynamic composition of Semantic Web Services oriented to eLearning application. Such methods will be the basis for creating special tools and middleware for developing a new generation of Learning Management Systems actively exploiting Service-oriented Computing paradigm.
- New methods for eLearning which will shift the current data and metadata-centric approaches to a dynamic functional-oriented approach based on Semantic Web Services technology. The activity scheme and support of information models for eLearning will shift the current data and metadata-centric approaches to a dynamic functional-oriented approach based on SWS technology. They will support dynamic creation and adaptation of learning objects, will address active authoring as learning activity and will investigate schemes for metadata organisation allowing pre- and post-use annotation of digital materials.
The main technological results of the project are:
- Development of a Semantic SOA Framework for creating eLearning application. Such a Framework will contain innovative user-friendly ontologically-based tools for creating, indexing and storing learning ontologies, eLearning Semantic Web Services and learning goals as well as specialised middleware for dynamic composition of such services. The Framework will significantly facilitate integration of SWS infrastructure with end-user applications and digital object repositories.
- Development a user-friendly ontology-based tools for semantic annotation of multimedia and learning objects compatible with SWS technology. Such tools will allow reusing of existing ontologies and semantic annotations of existing objects. They are oriented to make the labor-intensive process of constructing semantic annotation of learning objects, requiring expert knowledge of learning annotation standards and a specific ontology language, a task achievable by ordinary learning object developers.